World Bank Reprint Series: Number 173

Malcolm D. Bale and Ernst Lutz

Price Distortions in Agricultureand Their Effects:An International Comparison

Reprinted with permission from American Journal of Agricultural Economics, vol. 63, no. 1(February 1981), pp. 8-22.

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Reprinted fromArmERICAN JOURNAI, OF AGRICUL.TURAL ECONOMItCS

Vol. 63, No. 1, February 1981

Price Distortions in Agriculture and TheirEiffiects: An International ComparisonMalcolm D. Bale and Ernst Lutz

The central thesis of this paper is that aigricultural pricing policies pursued by developingcountries produce effects which are diametrically opposite to those produced by thepricing policies of many developed countries, and that the policies of both are costly interms of global welfare. In general, the agricultural sector in developing countries isheavily taxed while that In the developed countries receives substantial price protection.The effecis ofifagriculitral price distortions on output, consumption, trade, and ruralemployment are estimated for nine countries. In addition, the effects of price distortionson the disirihution of income between prodtucers and consumers, on government revenueand foreign exchange. and the net social losses of the policies are calculated.

Key.w words- .igricultmiiial policies, price distortions, social costs, trade intervention,%elftire analysis.

While in some parts of the world agricultural supports in developed countries maintain farmpolicy must deal with the problem of sur- incomes and lead to surpluses which in turnpluses, in other parts of the world-particu- find their way to developing country marketslarly in developing countries-agriculturail often on concessionzil terms, further depress-output is often insufficient to co-ver basic food ing domestic farm prices, and agricultural in-needs. The r-easons are many and v-aried, rang- puts are frequently either taxed or subsidized.ing from distribution and production Yet, the magnitude of the effects of these poli-techniques to political intervention at various cies on agricultural output, income distribu-levels in the global agricultural complex. tion between producers and consumers,While the most important reasons for in- efficiency, and on rural employment is oftenadequate agriiCultural output are difficult to as- not fully appreciated,certain, T. W. Schultz, in the first Elmhurst The ways in which governments can inter-Memorial Lecture to the International As- vene to alter market incentives in -agriculturesociation of AgricultUtral Economists. left no can be classified in three ways, based on theirdotibt as to his ranking of the causes. He impact on output (after SchLIltz 1978). First,stated that the level of agricultural production ther-e are economic policies that are neutraldepends not so much on technical consider- with respect to the opportunity cost of agricul-ations, but in lairge measure "on what govern- tural production. Second. there are thosements do to agriculture.'' (See also Schultz where agricultural pr-odtiction is overvalued.1977, 1978.) And, finally, there aie policies through which

It is well knowni that gyovernments intervene agricultural production is undervalued. Only ain the agriCtiltural price-setting mechanism in few countries meet the first classification (theymany different Nvays and for assotled reasons. are not ideentified here). Typically, high-For example. export taxes on agicultural income developed countries fall into the sec-products provide government revenue and ond category. In this study, we examirne Ja-help keep doomestic prices low, product price pan, West Germany, France, and Great Brit-

ain, countries where levies are placed onMalcolm D. Bale and I rnsi L,utz are cconomists with the [)e%el* grain imports, where imports of sugar, meat,opment Policy -S.diT of the Wm Id Bank. addiypout r etitdb uts

The authors .acknO%kledge helpful comments on an earlier ver- and datiry produc:ts re restricted by uotas.sion of this paper hy Willis Petcrson. Alan Harison. and an anon- and where, in the case of Japan, rice is gralIyymous reviewer. overpriced relative to world levels. The im-

The views and interpretations in this paper are those of the mediate consequences of these policies areauthors and should not he attributed to the World Bank. to itsaffiliated organizations, nor to any individual -.cling ill their behalf. overproduction and uinderlconsunmption of ag-

Copyright 1981 American Agricultural Econoniics Association

Bale and Lutz Agricuiltural Price Distrtiron' An nlterntiiondl (Comnparison 9

ricultural output. The third category typically pecuniary effects of agricultural price distor-is made up of low income developing nations. tions are analyzed using nominal protectionHere, as examples, we examine the pricing coefficients (NPCs) to mcasrlle the disparitypolicies of Thailand, Egypt, Argentina, and between domestic output prices and borderPakistan, where export taxes and price con- prices. Typical causes of price di'tortionstrols often undervalue agricultural output, re- evaluated here are producer price supports,sulting in underproduction. Many of these na- tariffs, quotas, export taxes, and overvallUedtions produce insufficient foodstuffs, and they exchange rates. Input subsidies for irrigationcannot afford to forego production oppor- water, fertilizer, and credit are not consideredtunities. In addition, we consider the case of because of the difficulty of obtaining cross-Yugoslavia, classified both as a developing country data and because of the impossibility,country and as a centrally planned economy in the case of water, of evaluating a "market"

This paper discusses government interven- rate when its costs and lifetime are Linknown.tion in the determination of agricultural prod- In each case, the intervention drives a wedgeuct prices, drawing on welfare theory to quan- between the domestic price and the world ortify the economic impacts on output, income "border" price. Domestic prices are defineddistribution, efficiency, and employment. The as the prices at farm and consumer levels,general theme is that the agricultural policies converted into U.S. dollars, using shadow ex-pursued by developing countries produce ef- change rates; border prices are the existingfects which are diametrically opposite to those "xs%orld" prices at the same point in the mar-of many developed countries, and that the pol- keting chain (i.e., the small country assump-icies of both are costly in terms of global wel- tion has been used). Border prices are used asfare. (A regent study which addresses the de- the point of reference for the evaluation be-velopii;g country side of this question in a cause they represent the opportunity cost ofsomewhat different manner is Peterson.) The the traded commodities. 2 They are also con-paper, begins with a description of the theoret- veniently available as they are observed in theical model on which the analysis is based and international marketplace. Nominal protectionthen continues by detailing the data sources: coefficients provide a measure of the disparityresults are presented in the next section, fol- between domestic prices and internationallowed by some concluding thoughts. prices, and are defined as

r Pd P, PuMethod and Theoretical Basis rE,. rP7

where Pd is domestic price, PuW is border price,The results of the paper are derived using and r is the equilibrium exchange rate.standard partial equilibrium comparative stat- The basic analytic structure of the model isic analysis in the Marshallian economic represented by equations (1) through (7):surplus framework. The method is well known (1) net social loss in productionfor both its usefulness and limitations. Details NSI -1/2 (Q - Q) (P, P )on this approach are not presented here, but / a 1 1 t t 2 QVthe reader is referred to Currie, Martin, and 1/2 t ns VSchmitz for an excellent review of the con- surplus and, by so doing, to validate its use as a tool of welfarecept, to Bale and Greenshields for an applica- economics," demonstrates theorctically that "consumers surplustion, and to Lutz and Scandizzo for a review is usually a very good appmirimaiion to thc appropnate welfaretion, and stoutz and can zr, revi e measures" (p. 589).O other studies.1 In ths paper, the real and 2 we recognize that the genera equilibrium effects of removing

price distortions on a global basis would alter border prices andtherefore alter the magnitude of the distorting effects. However, it

While the method is widely used, it is not without its detrac- is extremely difficult to estimate "shadow-free market prices" in ators. There is, in fact, a considerable body of literature and an first-best world, and we do not suppose that we will ever beongoing theoretical debate regarding the appropriatene's of using operating in a first- or even second-best environment.the underlying utility functions in evaluating welfare gains and In our analysis there are some cases where the use of the smalllosses across individuals or countries. The debate centers on country assumption may havc introduced a bias into our results.whether consumers' surplus analysis provides a measure of ben- Both for exporting countries and for importing countries ourefits and losses in terms of the "compensating variation" and the method may overestimate the true effects. This may apply to rice"equivalent variation" in the contemporary Hicksian form, in lhailand, cotton in Egypt. wheat in Japan and wheat in f-rance,Bergson clarifies this Uebate, finally noting that "despite theoreti- When some large countries are being considered simultaneously,cal criticism, practitioners have continued to apply surplus analy- the effects can be additive or they can cancel each other out. Forsis through the years . . . that must say something about the example, while the export taxes of some developing countries mayusefulness of such analysis" (p. 43). Willig, in a later article whose increase the world market price the import tariffs of some indus-* purpose is to settle the controversy surrounding consumers' trialized countries may depress it.

10 February 1981 Amer. J. Agr. Eco,t.

(2) net social loss in consumption (O0) dPr = dP [I + f'(P)],

NSL, = 1/2 (Cu. - C) (P, - Pu) where Pr is retail price, P is wholesale price,= 1/2 t, 2

nd W, and f(P) is marketing margin. The measured(3) welfare gain of producers change in consumers' welfare is

Gp = Q (Pp - P,,.) - NSLp, (I1) dP (C - 1/2dQ),4e cwhere C is consumption at domestic prices.

The actual change in consumers' welfare isG, = C (Pa. - P,) - NSLC, (12) dPr (C- 1/2dQ).

(5) change in foreign exchange earnings From equation (10), iff'(P) = 0, that is, ifdF = -PU (QU. - Q + C - C,,,), the marketing margin is constant, then the

welfare estimate is unaffected by the choice ofC6) change in government revenue price. If f'(P) > 0, implying that markups in-

dG = (NSLp + NSL,) - Gp G, crease as price increases, then the welfare ef--(1) - (2) - (3) - (4), and fect is understated. The same exercise may be

performed on the producer's side with the(7) change in rural employment same results. Thus, where it can be assumed

dL = dQ L/Q, that marketing margins are constant, no biasoccurs. At a practical level, the use of awhere Q, is production at world prices: Q, wholesale price can be justified on severalproduction at domestic prices; Ps, border groun(ds. MIvany products undergo transforma-prices; Pp,. price faced by domestic producers; tion into differenL products between thePr, price faced by domestic consumers;, t and wholesale and retail level. Thus, a single retailt., proportion of tariff in domestic price at the price does not exist for the product. This mayconsumer (t,) or the producer (t,) level; n,, be true for wheat, barley, maize, and beef inelasticity of domestic supply; nd, elasticity of many countries. In some developing coun-domestic demand; V, value of production at tries, where grains are used in households,P,; W, value of consumption at P,e. C,., con- wheat is subsidized such that wvholesale andsumption at world prices; C, consumption at retail prices are similar. Given these factors,domestic prices, and L/Q, labor/output we have been forced to compromise the idealcoefficient. and to use what is available,

Because border prices are used as the basisfor comparison, the domestic prices used mustcorrespond to the same point in the marketing Data Sourceschain. In calculating NPCs, farmgate prices indeveloping countries have been adjusted up- The base year of the analysis is calendar 1976.ward to take into account different transporta- The FAO Production Yea rbook was used as ation costs and marketing margins to the central source for production levels; imports and ex-market. (For specific details, see country case ports were obtained from the FAO Tradestudies referenced.) The prices used may Yearbook. Given the unavailability of data fortherefore be described as wholesale prices. consumptioni and stocks, particularly for de-For industrial countr-ies. wholesale prices as veloping countries, consumption was derivedrepolted: were used in the study. from production and tradle data, assuming the

In measuring the cost of protection, the use levels of stocks remained unchanged. Supplyof equivalent tariff levels-which are neces- and demand elasticities were taken fromsary for agricultural products facing many Rojko et al. In all cases they are long-run,nontariff barriers-means that production and general equilibrium elasticities, although hereconsumption effects are measured at the we suppress the cross-price terms.3 Becausewholesale level rather than at the farm and elasticity estimates differ widely from re-retail levels. This may result in the underesti-

mation of the foel fare costs. For example, The cross-price terms are small and cannot be used in standardconsider the following demand function: welfare analysis. We use the Rojko elasticity meastirements be-(8) Q =a -BPr, where cause they provide a . ornistent set of elasticities for the commod-

ities and countries ut.: here. Since elasticity cstimaites can differ(9) Pr = P + f(P), and we have used range analysis.

Bale and Lutz Agricultural Price Distortions: An International Comparison 11

searcher to researcher, and because we man-hours to full-time worker equivalents, inwished to demonstrate the sensitivity of the hours per year, are: France, 1,964; Germany,results to changes in elasticities, the supply 2,315; United Kingdom, 2,269; Japan, 2,450;and demand elasticities presented in table 1 Yugoslavia, 2,450; and developing coiintries,are ±0.5 times the point estimates given by 2,980. The basic data used in our analysis isRojko et al. shown in table l.

Nominal protection coefficients for develop- Our use of a rather simplistic nmodel of ruraling countries were derived from detailed coun- employment, and its change relative to output,try case studies by Bertrand (Thailand), Cud- is based on an input-output view of agricul-dihy (Egypt), Gotsch and Brown (Pakistan), tural production. This approach was used byReca (Argentina) and ULG Consultants Thorbecke, where the following equation was(Yugoslavia). In order to make adjustments estimated:for currency overvaluation, the nominal pro-tection coefficients were multiplied by the fol- = a0 + a1 Q.lowing ratios between the shadow exchange where E,, is employment in agriculture and Q.4rate and the official exchange rate of the dif- is agricultural output. Such an approach obvi-ferent countries as estimated by the World ously produces a constant labor-outputBank: Argentina, 0.8; Egypt, 0.69; Kenya,° coefficient, a shortcoming of any linear sys-0.76; Pakistan, 0.91; Portugal, 0.83; Thailand, tem, which in turn implies a constant marginal0.88; and Yugoslavia, 0.98. Shadow exchange physical product of labor. While more sophis-rates for developed countries are not esti- ticated models have been developed and esti-mated and are here assumed to be the same as mated by other-s (for example. Todaro), wemarket rates. have assumed constant input-output coef-

The nominal protection coefficients for de- ficients.veloped countries were calculated from dataof the International Wheat Council, Interna-tional Sugar Organization, U.S. Department Resultsof Agriculture (1979), and the World Bank.Note that despite the Common Agricultural We first consider the merchandise effects.Policy of the European Economic Community(EC), NPCs of members are not identical. Pruduction, Con%utniption, atndt Trade /felfetsThis is due to the "Monetary Compensatory Agricultural pAmounts" (MCAs) and "green" currencie's, gv pricing policies in developed andbecause of which internal EC exchange rates developing countries are significantly differ-in agriculture differ from official exchange ent. While prices for agricultural commoditiesrates. in developed countries generally have positive

Labor/Output Coefficients were con- rates of protection, in developing countriesstructed from Bartsch, Palacpac, International commodities are often taxed through price in-Cotton Advisory Committee, U.S Depart- tervention measures. As a result, the levels ofment of A-riculture (1978a, b), United King- agricultural production in industrialized na-dom Ministry of Agriculture, Forestry, and tions are higher than they would be withoutFisheriest and the European Communities intervention, whereas agricultural output inCommission. In the case of developing coun- less developed countries is significantlytries, marginal labor/output coefficients were smaller than what it would be in the abse.nce ofderived from a labor-intensive technology, distortions In the high elasticity case. Francesuch as hand harvesting with a buIllock-drawn and Germany, for example, are producing ancart and hand threshing. Aver-age coefficients increment of 4.3 and 2.8 million tons of wheat,are simply the average of coefficients taken respectively, because of price protection,from two or three different production tech- pwhereas in Argentina and Pakistan, produc-niques on irrigated and nonirrigated farms. In tion is discouraged, with a resulting estimateddeveloped countries, only average coefficients decrease of 7-0 and 1.3 million tons, respec-were available. Marginal coefficients in these tively (table 2).countries were assumed to be 1.5 times the average coeffilient for devlopcd Wountrie is broadly consistentaverage coefficients. 4 The conversion rates of with the Hayami and Ruttan e.,imale of 2.5 for a sample of

developing and developed countries. Clearly the inclusion ofhighly labor intensive technitities in developing countries makes

4 The assumption that marginal coefficients are 1,5 times the the Hayami and Riittan estimate higher than ours.

'0

Table 1. Basic Data Used for the Analysis, 1976

Range of Supply Range of Demand LaborBorder Elasticities Elasticities Coefficients

Country Price - - Produc- Consump-Commodity US$/mt NPC' Low High Low High tion tion Exports Average Marginal

France ------ ('000 metric tons)------ (Man-hours per ton)

Wheat 143 1.26 .42 1.28 -. 10 -. 30 16,150 7,785 8,365 25 37.5Maize 152 1.31 .17 .52 -. 20 -. 60 5,603 4,486 1,117 37 55.5Barley 137 1.39 .42 1.28 --.10 -. 30 8,530 5,637 2,893 25 37.5Sugar 289 1.35 .81 2.44 -. 12 -. 36 2,974 1,957 1,017 52 78.0Beef 2,365 1.27 .20 .60 .35 -1.05 1,821 1,706 115 40 60.0

GermanyWheat 143 1.49 .42 1.28 -. 10 -. 30 6,702 7,252 -550 25 37.5Maize 150 1.57 .17 .53 -. 20 -. 60 480 3,776 -3,296 37 55.5Barley 137 1.51 .42 1.28 -. 10 -. 30 6,487 7,973 -1,486 25 37.5Sugar 289 1.77 .43 1.30 - .08 -. 24 2,733 2,584 149 52 78.0Beef 1,970 1.42 .20 .60 -. 35 -1.05 1,365 1,435 -70 40 60.0

United KingdomWheat 156 1.15 .47 1.42 -. 10 -. 30 4,740 8,419 -3,679 25 37.5Maize 131 1.28 .45 1.35 -. 20 -. 60 2 3,720 -3,718 37 55.5Barley 132 1.01 .47 1.42 -. 10 - .30 7,648 8,096 -448 25 37.5Sugar 283 1.39 .22 .66 -. 10 -. 30 746 2.558 -1,812 52 78.0Beef 1,542 1.17 .20 .60 --. 35 -1.05 1,064 1,177 -113 40 60.0

JapanWheatb 189 2.81 .80 2.41 -. 08 -. 24 222 6,043 -5,821 54 81.0Barleyb 160 3.14 .80 2.41 -. 08 -e.24 210 1,971 -1,761 54 81.0Sugar 306 1.36 .21 .64 --. 11 -. 33 560 2,986 -2,426 110 165.0Beef 2,252 1.30 .33 .99 -. 40 -1.20 298 390 -92 58 87.0Rice 380 2.03 .08 .24 -. 06 -. 18 15,292 15,314 -22 185 277.5

YugoslaviaWheat 177 .54 .28 .75 -. 12 -. 37 5,979 5,118 861 25 37.5Maize 185 .71 .24 .72 -. 17 -. 52 9,106 8,647 459 37 55.5Beef 1,832 1.08 .20 .60 -. 40 - 1.20 326 266 60 40 60.0

ArgentinaWheat 136 .54 .25 .75 -. 05 -. 15 11,000 7,736 3,264 25 50.0Rice 194 .81 .27 .82 -. 10 -. 30 309 222 87 78 156.0Maize 118 .49 .22 .67 -. 11 -. 33 5,855 2,775 3,080 55 110.0Beef 927 .72 .25 .75 -. 20 -. 60 2,811 2,410 401 18 36.0

EgyptWheat 166 .48 .12 .37 -. 17 -. 52 1,960 4,878 -2,918 220 508.0 .Rice 375 .35 .25 .75 -. 12 -. 37 2,300 2,089 211 360 520.0Maize 171 .52 .06 .18 -. 12 -. 37 3,047 3,506 -459 240 480.0 sCotton 2,397 .34 .05 .15 -,10 - .30 396 231 165 8,440 10,000.0

PakistanWheat 152 .78 .17 .53 -. 20 -. 60 8,691 9,877 -1,186 247 533.0 ^Rice 320 .57 .15 .45 -. 15 -. 45 4,106 3,324 782 290 350.0 .Maize 171 .94 .10 ,30 -. 17 -. 52 764 764 0 300 480.0 'Cotton 876 .58 .82 2.47 -. 10 -. 30 418 305 113 2,240 3,950.0 .

ThailandRice 218 .74 .07 .22 -. 03 - .07 15,068 13,143 1,925 400 580.0 -Maize 115 1.02 .10 .30 -. 05 -. 15 2,675 287 2,388 240 480.0 >Sugar 298 1.65 .08 .24 -. 15 -.45 1,757 633 1,124 338 507.0Rubber 695 .49 .09 .28 -. 00 -. 02 400 27 373 54 81.0

Nominal protection coefficient.b These coefficients represent distortions in production only; the corresponding NTCs in consumption are 1.18 for wheat and .90 for barley.

3

Table 2. Real Effects of Price Distortions, 1976

Estimated Change in Agricultural EmploymentEstimated Change Estimated Change Estimated Change E Cg-

Country in Production in Consumption in Exports Average Coefficients Marginal Coefficients

Commodity Low High Low High Low High Low High Low High

('000 metric tons) - ------- (Full tn-ine workers) ------------France

Wheat 1,400 4,266 -161 -482 1,560 4,748 17,821 54,302 26,731 81,454Maize 225 689 -212 -637 438 1,326 4,239 12,980 6,358 19,470Barley 1,005 3,063 -158 -474 1,163 3,538 12,793 38,989 19,189 58,484Sugar 625 1,881 -61 -183 685 2,064 16,548 49,802 24,822 74,704Beef 77 232 -127 -381 204 613 1,568 4,725 2,352 7,088

Germany, F.R.Wheat 926 2,821 -238 -715 1,164 3,537 10,000 30,464 15,000 45,697Maize 30 92 -274 -823 304 915 479 1,470 719 2,206Barley 920 2,804 -269 -808 1,189 3,612 9,935 30,281 14,903 45,421Sugar 511 1,546 -90 -270 601 1,815 11,478 34,727 17,217 52,090Beef 81 242 -149 -446 229 688 1,400 4,181 2,099 6,772

United KingdomWheat 291 878 -110 -329 400 1,207 3,206 9,674 4,809 14,511Maize 0 1 -163 -488 163 489 0 16 0 24Barley 36 108 -8 -24 44 132 397 1,190 595 1,785Sugar 46 138 -72 -215 118 353 1,054 3,163 1,581 4,744Beef 31 93 -60 -180 91 272 546 1,639 820 2,459

JapanWheat 114 -74 -221 188 566 2,513 7,604 3,769 11,406Barley 114 "I 18 53 96 292 2,513 7,604 3,769 11,406Sugar 31 95 -87 -261 118 356 1,392 4,265 2,088 6,398Beef 23 68 -36 -108 59 176 544 1,610 817 2,415Rice 6,207 18,622 -466 -1,399 7,606 20,020 468,692 1,406,151 703,038 2,109,227

0:

b:

YugoslaviaWheat -1,273 -3,820 523 1,613 -1,796 -5,433 -12,990 -38,980 -19,485 -58,469Maize -893 -2,678 600 1,837 -1,493 -4,515 -13,486 -40,443 -20,229 -60,665Beef 5 14 -8 -24 13 38 82 229 122 343

ArgentinaWheat -2,343 -7,028 329 988 -2,672 -8,016 -19,525 -58,567 -39,050 -117,133Rice -20 -59 5 16 -25 -75 -520 -1,534 -1,040 -3,068Maize -1,341 -4,083 318 953 -1,658 -5,036 -24,585 -74,855 -49,170 149,710Beef -273 -820 187 562 -461 -1,382 -1,638 -4,920 -3,276 -9,840

EgyptWheat -255 -786 898 2,748 -1,153 -3,534 -18,700 -133,096 -43,180 -133,096 -Rice -1,068 -3,204 466 1,435 -1,533 -4,639 -128,160 -384,480 -185,120 -555,360 -Maize -169 -506 388 1,197 -557 -1,704 -13,474 -40,480 -26,987 -80,960 z

Cotton -38 -115 45 135 -83 -250 -106,907 -323,533 -126,667 -383,333 -

PakistanWheat -417 -1,299 557 1,671 -974 -2,971 -34,333 -106,951 -74,087 -230,789 n

Rice -465 -1,394 376 1,128 -841 -2,522 -44,950 -134,753 -54,250 -162,633 t:Maize -5 -15 8 25 -13 --40 -500 --1,500 -800 -2,400 CZCotton -248 -748 22 66 -270 -814 -185,173 -558,507 -326,533 -984,867 t

ThailandRice -371 -1,165 139 323 -509 --1,488 -49,467 -155,333 -71,727 -225,233Maize 5 16 0 - 1 6 17 400 1,280 800 2,560 -

Sugar 55 166 -37 -112 93 278 6,197 18,703 9,295 28,054 -Rubber -37 -117 0 1 -37 -117 -666 -2,106 -999 -3,159

a

16 Februqry 1981 Amer. J. Agr. Econ.

On the other hand, thie picture is reversed the primary sector in rural areas to indust.rialwith respect to consumption. Developing and service sectors in urban centers. Eco-countries consume more and developed coun- nomic theories on internal migration attributetries less than they would in the absence of this shift as a response to differences in em-price intervention measures. Thus the pricing ployment opportunities betwe n regions, Po-policies clearly have a beneficial effect in tential migrants evaluate costs and benefits as-terms of providing more food for the nonag- sociated with relocation and make their deci-ricultural population in developing countries. sion accordingly. A primary determinant inHowever, assuming that this result is one of their decision is the relative income oppor-the policy objectives of price intervention, it is tunities in rural versus urban locationsachieved at the expense of the agricultural sec- (Falaris). In spite of (or because of) massivetor. development efforts over the last decade, rural

The effects on trade are merely a combina- poverty persists in many parts of the world,'tion of the effects on production and coPsump- and recent work has demonstrated that lowtion, since stocks are asstumed to be constant. real-incomiie levels of farm houszholds have inIn general, we find that the pricing policies some cases declined (Rajaraman) at the samecause a reduction in the exports of developing time that various price-support measures arecountries (for exported commodities with maintaining farm incomes in other parts of theNPCs smaller than 1) and a lessening of im- world.ports by the industrialized nations (for im- A common explanation for rural poverty isported cormmodities with NPCs larger than that agricultural productivity is low because of1). In the case of imports by developing coun- tenatncy arrangements and limited access totries with NPCs of less than 1, these imports modern inputs and techniques such as con-are increased by the sum of the absolute val- trolled irrigaition, chemical fertilizers, pes-ues of the effects on production and consump- ticides, mechanizat'on, new varieties of crops,tion. Such a situation implies government sub- credit, and extension services. Such explana-sidies, for example, in Egypt for wheat and tions ignore the effect that product prices havemaize. (Parts of the imports may not be sub- on agricultural productivity and, therefore, onsidized directly by the government of Egypt employment and migration. Here we attemptbut may be the result of shipments at conces- to quantify the extent to which product pricessionary terms.) On the other hand, export that are undervalued contribute to a subopti-commodities with NPCs larger than 1 imply mal rural population and the extent to whichthat dumping is taking place and that export product prices that are overvalued contributesubsidies are necessary to bridge the gap be- to a larger-than-optimal rural population.tween the internial price and world market In table 2 we present four estimates of theprice. All five commnodities analyzed for impact of price distortions on agricultural em-France show the effects of this policy. ployment. Two are based on average labor/

On the basis of a small sample of countries, output coefficients, using production changesit is difficult to determine what the aggregate calculated from high and low supply elasticityeffects of agricultural policies are at the worlld estimates. The other two are calculated usingmarket level. Even for a -ttandard case in marginal labor/output coefficients where pro-which developing countries are exporters duction changes are based on high and lowusing export taxes and where developed coun- supply elasticities. There are three reasons fortries are importers with positive rates of pro- presenting the results in this manner. First, wetection, the sign of the impact on the world wish to demonstrate the sensitivity of em-market price cannot be determined a priori, ployment to changes in assumptions. Second,because both net exports and net imports are labor coefficients tend to be rather gross esti-being reduced at the same time. Hence, i. mates, as they are derived from numerouswould be necessary to analyze the policies of secondary sources that use different assump-all trading countries simultaneously for a par- tions and they typically vary by more thanticular commodity before the world market 100% within developing countries accolding toprice impact could be estimated. different production techniques for the s,ime

crop. Our results mnay be regarded as captur-E,rnpIo0'!net/iVJfigzran ,Effects

The process of econornic development typi- ... the most promising attack on employment problems indeveloping countrics is in efforts to redress the present urban bias

cally is associated with internal migration from in development strategies" (Edwards).

Bale and Lutz Agricutltural Price Distortions: An Intertnationial Comparison 17

ing the upper and lower bounds of employ- migration greater than the rates of urban jobment changes. Third, it can be argued that creation are serious problems in developingunder a regime of distortedI prices, marginal countries. While overt unemployment is pro-operators will be displaced orexpanded in re- nounced in urban centers, disguised unem-sponse to price changes. Thus, marginal ployment is prevalent in rulal areas (Todaro).labor/output coefficients are more appropriate Thus, any policies that contribute to unem-for estimating impacts on agricultural em- ployment or underemployment, such as ag-ployment. riculturi-i pricing policies, need to be exam-

Referring to the developed countries in table ined carefullv. The conventional lay wisdom2, we see that existing agricultural pricing pol- that if prices for farm products were to beicies cause significant numbers of workers to increased in developing countries, poor peopleremain in agriculture. Japanese rice-pricing would be hurt, needs to be scrultinized1. Manypolicies are particularly significant, causing of the poor are rural poor or former rural resi-from between one-half of a million workers dents who have migrated to urban areas in(low supply elasticity, average coefficient) to 2 search of better employment opportunities.million workers (high supply elasticity, margi- Higher agricultural prices wouid assist them ifnal coefficient) to stay in agriculture. As a they were to remain as farmers, landlessproportion of farm population, the numbers laborers, or farm-related workers. Viewed in aare large (2.1q to 9.6%); expressed as a pro- longer-run dynamic context, as farmers andportion of total population (0.4%r to 1 .9%), the farm laborers realize higher incomes, theirnumhers are still significant. In the European demand for urban-produced goods and ser-countries presented here, the number of vices will incteaise, so stimulating employmentworkers retained in agriculture is somewhat in urban areas.'smaller, both absolutely and relatively. Forexample, in France, if free-market prices were Welfirc LI/7e(to prevail for all five commodities, between52,987 and 241,200 workers in an agricultural Our results indicate that the econormics of thelabor force of 8,6 million would be displaced. 6 countries analyzed incur large annual welfareIn terms of the total work force, the propor- losses due to a misallocation of resources re-tion is 0.16% to 0.75%4. While this percentage suIlting fiom the existing agriCultural pricilngmay seem rather small, it is nonetheless sig- policies (table 3). The losses depend linearlynificant. on assumeCd elasticities and quadratically on

In developing countries, agricultural price the size of the price distortion as measured bydistortions have the effect of reducing farm a proportional tariff rate, Total net socialemployment from that which would exist losses are the sum of net social losses in pro-under free market prices. In general, the abso- duction and in consumption. They range fromlute value of the effects on employment is U.S. $26 million for the United Kingdom (thelarger for developing than for developed coun- low elasticity case) to UJ.S. $4,119 million fortries, pardly because of the labcor-intensive Japan (the high elasticity case). Even thoughproduction methods used in developing coun- the sample of commodities used in this analy-tries. The numbers suggest the extent to which sis is smalli, it is interesting to conmpar-e theprice distortions create unemployment and estimrated welfare losses to the GINP of thestimulate migration. Using the high supply countries. T'he results show that in compalri-elasticity and marginal labor coefficients in son witlh economic otutpuit, distortions areEgypt, for example. the total reduiction in ag- generally more costly to developing countriesricultLiratl employment for the four commod- than to industrialized nations (table 4). Com-ities is 1.15 million workers, or around 5% of pared to agricultural gross national productthe rural population. IEmployment in rice pro- (GNP), however, the comparative losses ofduction accounts for a large portion of this, No the different countries are Somewhat moredoubt the numbers would be considerably evenly distributed when the importance of thelarger if secondary (multiplier) effects were agricultural sector in the total economy isconsidered and if all commodities were cov- taken into acCounLt.ered. The results have been obtained from a pa,-

Unernployment and rates of rural-to-urban We are indebted to Wili%S Peterson for %uggetling this point.8By wlecting only four or five major agncultural tormmodliie,

6 We do not wish to render the labor estilnales useless by here, we clearly underestimate the c lTcct' of the price dio%rwionspresenting numbers which have such a large variance, but we do in the agricultur.al sector. Thus, our figures represent lowerwant to present realistic upper and lower bounds. bounds of the true effects.

Table 3. Net Social Losses of Price Distortions, 1976 (in '000 US dollars)

Net Social Loss Net Social Loss TotalCountry in Production in Consumption Net Social Loss

Commodity Low High Low High Low High

FranceWheat 26,020 79,298 2,986 8,959 29,006 88,258Maize 5,310 16,244 5,002 15,006 10,313 31,250Barley 26,854 81,840 4,225 12,676 31,079 94,515Sugar 31,586 95,148 3,079 9,238 34,665 104,386Beef 24,721 74,163 40,530 121,589 65,251 195,752

Total 114,491 346,693 55,822 167,468 160,314 514,161

Germany, F.R.Wheat 32,341 98,839 8,355 25,066 40,696 123,905Maize 1,266 3,948 11,721 35,1(4 12,988 39,112Barley 32,147 97,973 9,408 28,223 41,555 126,196Sugar 56,883 171,973 10,006 30,018 66,889 201,990Beef 33,405 100,214 61,456 184,369 94,861 284,583

Total 156,042 472,947 100,946 302,840 256,t1?89 775,786

United KingdomWheat 3,400 10,272 1,285 3,854 4,685 14,126Maize 4 11 2,985 8,955 2,988 8,965Barley 23 71 5 16 29 87Sugar 2,541 7,623 3,961 11,882 6,502 19,506Beef 4,053 12,158 7,845 23.536 11,898 35,694

Total 10,021 30,135 16,081 48,243 26,102 78,378

JapanWheat 19,567 58,946 1,254 3,763 20,821 62,709Barley 19,602 59,051 140 420 19,742 59,471Sugar 1,715 5,225 4,789 14,367 6,504 19,592Beef 7,666 22,998 12,161 36,482 19,827 59,480Rice 2,035,883 3,644,244 91,237 273,712 2,127,120 3,917,956

Total 2,084,433 3,790,464 109,581 328,744 2,194,014 4,119,208

YugoslaviaWheat 51,836 155,509 21,298 65,670 73,135 221,179Maize 23,945 71,836 16,106 49,266 40,051 121,102Beef 354 1,062 578 1,733 a_1 2,794

Total 76,135 228,407 37,982 116,669 114,117 345,075

ArgentinaWheat 73,276 2i9,829 10,307 30,920 83,583 250,749Rice 361 1,095 96 288 457 1,383Maize 40,341 122,856 9,560 28,680 49,901 151,536Beef 35,468 106,403 24,327 72,980 59,794 179,383

Total 149,446 450,183 44,290 132,868 193,735 583,051

EgyptWheat 10,997 33,908 38,773 118,601 49,771 152,509Rice 130,145 390,435 56,739 174,944 186,884 565,380Maize 6,926 20,777 15,938 49,143 22,864 69,920Cotton 30,403 91,208 35,470 106,409 65,873 197,618

Total 178.471 536,328 146,920 449,097 325,392 985,427

PakistanWheat 6,968 21,723 9,316 27,947 16,283 49,670Rice 31,966 95,899 25,878 77,635 57,845 173,534Maize 25 75 43 130 68 205Cotton 45,660 137,536 4,063 12,189 49,723 149,725

Total 84,619 255,233 39,300 117,90)1 123,919 373,134

ThailandRice 10,503 33,008 3,926 9,161 14,429 42,169Maize 6 18 0 1 6 19Sugar 5,363 16,088 3,623 10,868 8,985 26,956Rubber 6,641 20,659 0 100 6,641 20,759

Total 22,513 69,773 7,549 20,130 30,061 89,903

Bale and Lutz Agrcultural Price Distortions: An International Comparison 19

Table 4. Estimated Total Net Social Losses as a Percentage of GNP for Some Countries and for aSelected Commodity Sample, 1976

Social Losses Social Losses

Agricultural GNP" (95 of GNP) (95 of Agricultural GNP)

(as ( of GNP) Low High Low High

France 5 0.05 0.16 1.0 3.2

Germany 3 0.06 0.19 2.0 6.3United Kingdom 3 0.01 0.04 0.3 1.3Japan 5 0.43 0.80 8.6 16.0

Yugoslavia 16 0.34 1.03 2.1 6.4

Argentina 13 0.48 1.46 3.7 11.2Egypt 28 3.52 10.58 12.6 37 8Pakistan 33 1.01 3.04 3.1 9.2Thailand 27 0.21 0.62 0.8 2.3

World Bank 1979.

tial equilibrium model and hence capture only tioned, the quota recipient gets the revenue.partial effects. However, it is clear that distor- So, in general, our results tend to overestimatetions of the size discussed here would have government revenues. Exceptions are thoserepercussions in other sectors of the economy countries that import commodities with NPCsas well. Thus, a general equilibrium analysis of less than one (e.g., wheat in Pakistan), inwould produce estimates of social costs larger which case our method assumed inmplicitlythan those estimated here. that the entire distortion is due to government

As our results in table 5 indicate, the most subsidies. To the extent that imports at con-sizeable effects of the different agricultural cessionary terms are involved, our results un-policies are the welfare transfers between con- derestimate actual government receipts.sumers and producers. While the farm sector The effects on foreign exchange earningsin the developing countries studied was taxed are again clearly divided according toi differentfrom about $700 million to about $2 billion levels of development. While industrializedannually, the producers in developed coun- nations gained foreign exchange through pro-tries received large transfers due to the protec- tectionisi policies, developing countries losttionist policies. In Japan, where the average foreign exchange earnings. This is particularlyrate of protection is the highest, farmers serious in that foreign exchange availabilitiesgained between $2.6 and $5.1 billion for the represent a major bottleneck for developingtotal of the five major commodities analyzed. countries in their efforts to increase growth(See Bale, who estimates the producer gain to and alleviate poverty.farmers for these products, except sugar, at$5.29 billion in 1975/76.) Consumers in devel- lSinitlhions.oped countries incurred large welfare lossesbecause of price protection whereas the con- Two caveats need to be made in order to in-sumers in developing countries generally sure proper interpretation of our results. First,gained from this type of price intervention. the results atre based on only one year--1976.Relating the magnitudes of the welfare trans- Second. in certain cases the quality of the datafers to the size of the social losses, it is appar- is uncertain and some personal judgmentsent that the transfers are far more sizeable were required. Because of the uncer-taintiesthan the deadweight losses. involved, range analysis was used to ascertain

Our results indicate that, with the exception the sensitivity of the results to different dataof France, governments in all countries re- input. We regard the results as providing or-ceived increased revenues from their interven- ders of magnitude rather than exact measLures.tionist policies. These results are based on the As indicated by the range analysis, the q4ialita-implicit assumption that the entire price dis- tive conclusions are stable with respect to dif-tortion is attributable to taxes (or subsidies). ferent elasticity assumptions. MethodologicalIn reality, however, quantitative restrictions questions were addressed in a previous sec-also are used, and unless the quotas are auc- tion.

Table 5. Monetary Effects of Price Distortions 1976 (in '000 U.S. Dollars)

Welfare Gain of Welfare Gain of Change in ForeignProducers Consumers Change in Exchange Earnings

Country GovernmentCommodity Low High Low High Revenue Low High

FranceWheat 574,437 521,159 --292,433 -298,405 311,011 223,124 678,904Maize 258,703 447,769 -216,382 -226,387 - 52,633 66,533 201,615Barley 428,904 373,918 -305,410 -1313,861 154,573 159,379 484,695Sugar 269,234 205,672 201,030 207,188 102,870 198.088 596.491Beef 1,138,079 1,088,637 -1,129,896 - 1,210,955 73,433 483,337 1,450,011

Total 2,669,357 2,437,155 -2,145,151 --2,256,796 694,520 1,130,461 3,411,716

GermanyWheat 437,178 370,771 --516,503 -533,214 38,539 166,477 505,734Maize 39,774 37,092 334,569 --358,012 281,808 45,571 137,236Barley 421,099 355,273 566,481 585,296 103,827 162,961 494,886Sugar 551,291 436,202 -585,023 605,035 --33,157 173,738 524,650Beef 1,095,996 1,029,187 -1.248,775 1,371,688 57,918 451,720 1,355,159

Total 2,545,338 2,228,525 --3,251,351 -3,453,245 448,935 1,000,467 3,017,665

United KingdomWheat 107,516 100,644 - 198,289 -200,859 86,089 62,462 188,350Maize 70 63 139,434 --145,404 136,376 21,346 64,038Barley 10,072 10,024 - 10,692 -- 107.03 591 5,756 17,368Sugar 79,795 74,713 286,287 294,209 199,990 33,343 100,029Beef 274,864 266,,759 316,384 332.075 29,622 139,976 419,928

Total 472,317 452,203 951,086 983,250 452,668 262.883 789,713

JapanWheat 56,377 16,998 -206,837 209,346 129,639 35,532 106,974Barley 52,302 12,853 31,396 31,116 103,440 15,360 46,720Sugar 59,975 56,464 -333,727 -343,305 267,248 36,131 108,846Beef 193,663 178,331 --275,645 -299,966 62,155 132,179 396,536Rice 4,770,541 2,341,044 6,085,137 --6,267,611 8,611 2,535,894 7,607,682

Total 5,132,858 2,605,690 --6,869,950 --7,089.112 364,213 2,755,096 8,266,758

YugosiaviaWheat -538,646 -642,319 395,409 351,038 70,103 317,977 961,647Maize -512,482 --560,372 447,805 414,645 24,625 -2-76,217 -835,184Beef 47,425 46,717 - 39,563 --40,718 -8,794 23,287 69,860

Total - 1,003,703 --1,155,974 803,651 724,965 85,934 570,907 --1,726,971

ArgentinaWheat --761,436 - 907,989 473,658 453,044 204,196 -363,404 --1,090,212Rice - 11,750 - 12,845 8,087 7,895 3,207 --4,807 -- 14,561Maize --392,695 -475,210 157,440 138,320 185,354 - 195,689 -594,259Beef - 765.091 -836,027 601,213 552,560 104,084 427,102 --1,281,307

Total 1,930,972 - 2,232,071 1,240,398 1,151,819 496,841 991,002 2.980,339

EgyptWheat -180,184 -203,095 382,296 302,468 251,882 191,425 --586,573Rice 690,770 -951,060 452,455 334,249 51,431 575,027 -1,739,630

aiz7e 2.57,024 270,875 271,834 238.63(0 37,675 95,266 291,333Cotton 656,883 -717,688 329,977 259.037 26I,0)31 199,614 598,841

Total - 1,784,861 2,142,718 1,436,562 1,134,384 22.90(7 1,061.332 3,216,177

PakistanWheat --297,595 312,350 120,971 302,340 --39,660 -148,031 --451,544Rice -- 596,952 - 660,884 431,504 379,748 107,603 -269,044 -807,133Maize - 7,864 -7,914 7,796 7,709 0 --2,252 -6,838Cotton - 199,450 -291,327 108,153 100,027 41,575 -236,776 --712,978

Total -1,101,861 -1,272,475 868,424 789,824 109,518 895,665 1,978.493

ThailandRice 864,557 ---887,062 741,019 735,784 109,109 110,989 324,376Maize 6,146 6,134 --660 ---661 ---5,492 636 1,907Sugar 334,968 324,243 -126,235 -- 133,480 --- 217,719 27,647 82,942Rubber -- 148,421 -162,439 9,570 9,471 132,210 -26,041 81,408

Total -671,864 -719,124 623,694 611,114 18,108 -108.747 -320.935

Bale and Lutz Agrictultural Price Distortions: An International Comparison 21

Conclusions Bartsch, W. H. Em.'plovinent and Techttology Choice inAsian Agricult:are. New York: Praeger Publishers,

What emerges from this paper is the vital role 1977.that farm product prices play in achieving op- Bergson, A. "A Note on Consumers' Surplus." J. Econ.timum output and growth in productivity. Be- Lit. 13(1975):38-44.

u incorrect price signals are being Bertrand, T. J. Thailand-Case Studv ofj Agricultural

given to farmers, full potential in terms of allo- Pap. No. 38W, 1980.cation, production, and consumption is not Cuddihy, B. Agricultural Price ainwetinen in Egypt,.being realized. In many cases, the estimated World Bank Staff Work. Pap. No. 388, 1980.changes in production have greatly altered Currie, J. M., J. A. Martin, and A. Schmitz. "The Con-trade patterns, in some cases causing import- cept of Economic Surplus and Its Use in Economicing countries to become self-sufficient, in Analysis.'" Econ. J. 81(1971):741-99.other cases causing "would-be exporters" to Edwards, E. O., ed. Employment in D)eveloping .Val,io,,.become importers. Particularly the magnitude New York: Ford Foundation, 1974.of income transfers but also that of the Euiropean Communitiec Commission. Earning.s ini Ag-

effiieny loses(netsocal lsse) ar si riculture. Brussels, 1976.efficiency losses (net social losses) are sig- Falaris, E, M. "The Determinants of Internal Migration innificant, both as an absolute number and as a Peru: An Economic Analysis." PEcon. Devel. aind

proportion of national and agricultural in- Cultur. Change 27(1979):327-41.come. The effects of price distortions on rural Gotsch, C. H., and G. T. Brown. Prices, Taxes. aindemployment, while perhaps less impressive Stubsitdies itn Pakistan Agriculture. World Bank Staffthan the welfare losses, are nonetheless seri- Work. Pap. No. 387, 1980.ous, given the high unemployment rates in Hayami, Y., and V. Ruttan. A*g,icuotural Dvi-'lopintuit:developing countries and the political sensitiv- .4An Interalatanl Perspective. Baltimore, Md.: Johnsity of agricultural employment in developed Hopkins University Press, 1971.countries. Since we have not considered dis- International Cotton Advisory Comimittee. Survey (}fCost

oJ'IProduction ot Rawi Cotton. L.ondon, 1975, 1976.tortions in the input markets our analysis may international Sugar Organization. Sugar Yearbook. Lon-overestimate or underestimate the true wel- don, 1977.fare effects depending on the nature of the International Wheat C'ouncil. World Whieat Statigstics.input distortion (subsidies or taxes) and London, 1978.whether the nominal protection coefficients Lutz, E., and P. L. Scandizzo. "Price Distortions in De-are greater or less than one. veloping Countries: A Bias against Agriculture."

The ultimate question about agricilttiral Europ. Rev. Agr. Econ., in press.pricing policies is their long-term dynamic ef- Palacpac. A. C. World Ri c Statistics. Los Banos, Philip-fects. In this pap iwe have quantified the pines: International Rice Research Institute, 1978.static effects. Our model (and the state of Peterson, W. L. "International Farm Prices and the So-statc efect~. ur mdel(andthestat of cial Cost of Cheap Food Policies." Amter. J. Agr.technology of our profession) did not allow us Econ. 61(1979):12-21.to estimate accurately the effects on income Rajaraman, 1. "Poverty, Inequality and Economicand industrial growth, adoption of technology, Growth: Rural Punjab." J. Del el. Stdl.investment in agriculture, social conse- 11(19750:278-90.quences, and others. While it is politicians and Reca, 1. G. .-Itye Inrinr : ('ountry Case Stuttd oJf Agricul-not agricultural economists who make the de- tira(il Prices tintl Subsidies. World Bank Staff Work.cisions for governments, our profession plays Pap. No. 386, 1980.a vital role in defining and quantifying the is- Rojko, A., et al. Alternati'e Ftxuures jiTr Itorldf F'ood insues involved, and in passing these findings to 1985. Washington. 1).('.: U.S. Department of Ag-appropriate officials. Our hope is that this riculture ESCS For. Agr. licon. Rep. No. 146, 1978.paper is in keeping with that tradition. Schultz, T. W. ''Constraints on Agrictulturial Produtlion'

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